SMART Irrigation Controllers How smart are they?

Transcription

1 SMART Irrigation Controllers How smart are they? Loren Oki Dept. of Plant Sciences and Dept. Human Ecology UC Davis Make Every Drop of Water Count USGBC CC Fresno, CA June 28, 2017

2 Topics Irrigation objectives What are SMART controllers? Types of SMART controllers How do they work? 2

3 Irrigation Objectives Maximize water use efficiency Apply only the amount the plants need Applied so that it is accessible by plants Scheduled to optimize the interval between irrigations (wetted soil depth) 3

4 Irrigation Objectives Information needed To determine valve run time: Soil type (plant available water) Depth to wet DU- Distribution Uniformity PR- Precipitation (application) Rate To determine when to irrigate: K L - Landscape Coefficient ET 0 - Reference ET 4

5 What are SMART controllers? Smart sensors and controllers monitor weather and other site conditions and adjust the irrigation system to apply just the right amount of water at just the right time. Irrigation Association 5

6 What are SMART controllers? Smart sensors and controllers monitor weather and other site conditions and adjust the irrigation system to apply just the right amount of water at just the right time. Irrigation Association 6

7 Types of SMART controllers Weather-based Soil moisture-based 7

8 Types of SMART controllers Weather-based Manages irrigation based on weather conditions Signal Weather data from central source Historical Preprogrammed with local climate data On-site measurement Weather station on location University of Florida Smart Irrigation Controller Series 8

9 Weather-Based Weather-based irrigation controllers adjust the irrigation system s station run times based on plants watering needs rather than on a preset, fixed schedule. from: EPA s WeatherSense Labeled Weather-Based Irrigation Controllers. What s wrong with this statement? 9

10 Weather-Based Weather-based irrigation controllers adjust the irrigation system s station schedule based on an estimation of plants watering needs rather than on a preset, fixed schedule. This is more correct. - Run times should not be modified. - The ET method is an estimation of plant water needs. 10

11 Weather-Based How they work How to determine How much to apply When to apply 11

12 Weather-Based How they work How to determine how much to apply Need to know: Soil type Plant Available Water Depth to wet 12

13 Soil Information Depth to wet (in.): 12 Infiltrationmid rate * (in./hr) Plant Avail Water- mid (%) ** Irrig to wet to depth (in) Soil Texture Coarse sand / fine sand loamy sand Moderately Coarse sandy loam Medium loam silty loam silt Moderately Fine sandy clay loam clay loam silty clay loam Fine sandy clay silty clay clay *Also known as intake rate. Mid values in the range. **IA Landscape Irrigation Auditor Manual page 177. Mid value in the range. assume 50% dry down (managed allowable depletion) 13

14 Weather-Based How they work Determine how much to apply Amount to apply= PAW Depth to wet MAD PAW=Plant Available Water MAD= Managed Allowed Depletion (how much water to be used) Amount to apply= =

15 Weather-Based How they work Determine how much to apply (1.2 ) Determine runtime From catch can assessment DU (ex: 0.75) Precipitation Rate (ex: 0.4 in/hr, rotors) Run time = Amt to apply PR ( DU ) = ( ) = 3.5 hrs 15

16 Weather-Based How they work Determine how much to apply (1.2 ) Determine runtime (3.5 hrs) How to determine when to apply 16

17 Weather-Based How to determine when to apply Require weather or ET 0 data What is ET 0? Reference Evapotranspiration The amount of water used by the reference crop (transpiration) and losses directly from the soil surface (evaporation) Needs to be modified to landscape conditions 17

18 Climate CIMIS C alifornia I rrigation M anagement I nformation S ystem Collects weather info Estimates plant water use More than 120 stations Water use reports are used with a crop or landscape coefficient to estimate site water use 18

19 Weather-Based How it works for crops Reference ET (ET 0 ) is reported by CIMIS Crop coefficient (K C ) is necessary Determine crop ET (ET C ) to estimate water use so, ET C =ET 0 x K C Example: citrus orchard K C = 0.65 If ET 0 for the past 5 days= 1.75, then Citrus crop water use was 1.75 x 0.65 =

20 Weather-Based How it works for landscapes Reference ET (ET 0 ) is reported by CIMIS Landscape coefficient (K L ) is necessary Determine landscape ET (ET L ) to estimate water use so, ET L =ET 0 x K L Example: moderate water use landscape zone K L = 0.4 If ET 0 for the past 5 days= 1.75, then Landscape water use was 1.75 x 0.4 =

21 Weather-Based How they work The amount of water to apply is 1.2 Landscape water use for the past 5 days was 0.7 (from: 1.75 x 0.4 = 0.7 ) The controller retrieves or calculates ET 0 and determines ET L each day ET L is accumulated When the accumulated ET L reaches 1.2, Irrigation is initiated 21

22 Weather-Based So, how do they REALLY work? Information the controller needs Weather to determine ET 0 Historical (see CIMIS) From on location weather station From central source (web, tel, etc.) 22

23 Weather-Based Information the controller needs Weather to determine ET 0 or ET 0 Landscape zone to determine K L Turf, shrubs, trees, etc. Water use 23

24 Weather-Based Information the controller needs Weather to determine ET 0 Landscape zone to determine K L Irrigation system to determine PR and DU Spray, rotor, drip From: Netafim 24

25 Weather-Based Information the controller needs Weather to determine ET 0 Landscape zone to determine K L Irrigation system to determine PR and DU Soil type to determine PAW Slope to prevent runoff From this, the program estimates the specific information it needs to do the calculations presented earlier. 25

26 Water Budget Adjustment (percent adjustment) To reduce irrigation as a fraction of that applied in the driest period July has the greatest ET rates See CIMIS Reference ET Zones map 26

27 Irrigation Systems 27

28 Water Budget Adjustment (percent adjustment) Monthly Average ET (inches/mo) Zone ZoneJanJan Feb Feb Mar Mar Apr Apr May Jun Jul Aug Sep Oct Oct Nov Nov Dec DecTotal Total

29 Water Budget Adjustment (percent adjustment) Monthly Average ET (inches/mo) Zone Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total % 24% 42% 63% 85% 97% 100% 88% 67% 46% 22% 12% 29

30 Water Budget Adjustment (percent adjustment) Monthly Average ET (inches/mo) Zone Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total % 24% 42% 63% 85% 97% 100% 88% 67% 46% 22% 12% So how does a controller make the adjustment? 30

31 R Water Budget Adjustment (percent adjustment) Monthly Average ET (inches/mo) Zone Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total % 24% 42% 63% 85% 97% 100% 88% 67% 46% 22% 12% So how does a controller make the adjustment? Use the percentage to reduce station Run time Landscape coefficients (K L ) 31

32 Water Budget Adjustment (percent adjustment) Monthly Average ET (inches/mo) Zone Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total % 24% 42% 63% 85% 97% 100% 88% 67% 46% 22% 12% So how does a controller make the adjustment? Use the percentage to reduce station Run time Landscape coefficients (K L ) YES! RIGHT WAY! 32

33 Types of SMART controllers Weather-based Soil moisture-based Manages irrigation based on soil moisture condition Requires sensors in the soil 33

34 Soil Moisture-Based Applies water based on the amount of water in the soil When dry, apply water If not dry, don t irrigate Can also shut off valve as soil is rewetted 34

35 Soil Moisture-Based Types Bypass/interruption Does not allow irrigation if soil is wet Initiate/terminate Starts irrigation when dry Ends irrigation when soil is rewetted 35

36 Soil Moisture-Based Sensor types Volumetric Water Content The amount of water Matric potential How tightly the water is held in the soil It s important to know the difference 36

37 Moisture Retention Curve All soils have a characteristic curve Graphic: Brady & Weil, The Nature and Properties of Soils,

38 Soil Moisture-Based Sensor types Volumetric Water Content The amount of water Depends on soil texture Matric potential How tightly the water is held in the soil More important in plant-water relations 38

39 Sensors Soil Moisture-Based Granular matrix sensor Watermark 39

40 Sensors Soil Moisture-Based Tensiometer 40

41 Sensors Soil Moisture-Based Time Domain Reflectometry (TDR) Time Domain Transmissometry (TDT) 41

42 Sensors Soil Moisture-Based Frequency Domain (FD) Photo: L. Oki Conductance-based sensors are NOT appropriate 42

43 Soil Moisture-Based Sensors- Be aware of what is measured Matric Potential Granular matrix sensor Tensiometer Volumetric Water Content TDR, TDT FD 43

44 Irrigation objectives What are SMART controllers? Types of SMART controllers Weather Soil moisture Topics How do they work? 44

45 But Which are the good ones? Which ones are recommended by the University of California? 45

46 Manufacturers (of controllers with 20 stations or fewer) Brilliant Technologies Cyber-Rain Desert Irrigation H20 Hunter HydroPoint Hydro-Rain Irritrol Nxeco OnPoint Orbit Rachio Rain Bird Raindrip RainMachine RainMaster RainPal Signature SkyDrop Toro Weathermatic 46

47 Thank you Photo: L.Oki